Secure Data Transmission Scheme Based on Elliptic Curve Cryptography for Internet of Things

Harbi, Yasmine; Aliouat, Zibouda; Harous, Saad; Bentaleb, Abdelhak

doi:10.1007/978-3-030-05481-6_3

Cited by 9 publications

(25 citation statements)

References 19 publications

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“…Wherein, 𝜔 f denotes the output function, and 𝜂 i symbolizes the weight value. Finally, the loss function (LF) is computed for the output value as in (23).…”

Section: Softmax Layermentioning

confidence: 99%

A secure data transmission and efficient data balancing approach for 5G‐based IoT data using UUDIS‐ECC and LSRHS‐CNN algorithms

et al. 2022

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Due to the realization of 5G technology, the Internet of things (IoT) has made remarkable advancements in recent years. However, security along with data balancing issues is proffered owing to IoT data's growth. The universally unique identifier short input pseudo‐random (SiP) hash‐based elliptic curve cryptography (UUDIS‐ECC) centred secure data transfer (DT) and linear scaling Rock Hyraxes swarm‐based convolutional neural network (LSRHS‐CNN) centred 5G IoT data balancing are proposed here to address those issues. Authentication, destination selection, validation, secure DT, and also load balancing are the proposed method's five phases. Initially, during the registration phase, the Length Nano ID (LNanoID) is created in the authentication. The user is permitted to further communicate if the LNanoID is matched with the already saved LNanoID. The destination is selected if the user is authorized. Utilizing the sender and the receiver's public key, the hash code is produced in the validation centre by the SiP hash function after destination selection. After that, by employing the UUDIS‐ECC algorithm, the IoT data is safely transmitted towards the destination. The 5G IoT data is balanced by using the LSRHS‐CNN algorithm during DT. Superior results are attained by the proposed methods analogized to existing research methods.

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“…Wherein, 𝜔 f denotes the output function, and 𝜂 i symbolizes the weight value. Finally, the loss function (LF) is computed for the output value as in (23).…”

Section: Softmax Layermentioning

confidence: 99%

A secure data transmission and efficient data balancing approach for 5G‐based IoT data using UUDIS‐ECC and LSRHS‐CNN algorithms

et al. 2022

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“…The major advantage of Homomorphic encryption is allows complex mathematical operations to be performed on encrypted data without know the contents of the original plain data [22]. As calculations are performed on encrypted texts, the data privacy and confidentiality are protected [23].…”

Section: Setup and Key Generation Phasementioning

confidence: 99%

“…So that we can ensures the content exchanged between the Medical Sensors and Medical Server is protectedagainst any modification by malicious or unauthorized users, and moreover to allow the Medical Server to determine the evil data, we uses the homomorphic Message Authentication Code (MAC) scheme, in order to provide data integrity. MAC ensures that received message is from the authenticated source and it is not tempered by any third party during transmission [23].…”

Section: Setup and Key Generation Phasementioning

confidence: 99%

“…Therefore, our proposed scheme provides good confidentiality for patient's health data, i.e., it protects the users' privacy data patient's. The security proof of the homomorphic encryption is provided in [22,23].…”

Section: Security Analysismentioning

confidence: 99%

“…The Aggregator calcute the aggregat on encrypted data without know the contents of the original data. The security proof of HMAC is provided in [23]. Hence, an adversary will be unable to generate a valid HMAC unless he/she knows the secret key that is shared between the Medical Sensors and the Medical Server.…”

Section: Security Analysismentioning

confidence: 99%

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EPPDA: An Efficient and Privacy-Preserving Data Aggregation Scheme with Authentication and Authorization for IoT-Based Healthcare

Almalki

Soufiene

2021

Preprint

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Internet of Things (IoT) connects various kinds of intelligent objects and devices using the internet to collect and exchange data. Nowadays, The IoT is used in diverse application domains, including the healthcare. In the healthcare domain, the IoT devices can collects patient data, and its forwards the data to the healthcare professionals can view it. The IoT devices are usually resource-constrained in terms of energy consumption, storage capacity, computational capability, and communication range, data aggregation techniques are used to reduce the communication overhead. However, in healthcare system using IoT, the heterogeneity of technologies, the large number of devices and systems, and the different types of users and roles create important challenges in terms of security. For that, the security and privacy aggregation of health data are very important aspects. In this paper, we propose a novel secure data aggregation scheme based on homomorphic primitives in IoT based healthcare systems, called “An Efficient and Privacy-Preserving Data Aggregation Scheme with authentication for IoT-Based Healthcare applications” (EPPDA). EPPDA is based the Verification and Authorization phase to verifying the legitimacy of the nodes wants to join the process of aggregation. EPPDA uses additive homomorphic encryption to protect data privacy and combines it with homomorphic MAC to check the data integrity. The security analysis and experimental results show that our proposed scheme guarantees data privacy, messages authenticity, and integrity, with lightweight communication overhead and computation.

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Security of internet of things based on cryptographic algorithms: a survey

et al. 2021

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Secure Data Transmission Scheme Based on Elliptic Curve Cryptography for Internet of Things

Cited by 9 publications

References 19 publications

A secure data transmission and efficient data balancing approach for 5G‐based IoT data using UUDIS‐ECC and LSRHS‐CNN algorithms

A secure data transmission and efficient data balancing approach for 5G‐based IoT data using UUDIS‐ECC and LSRHS‐CNN algorithms

EPPDA: An Efficient and Privacy-Preserving Data Aggregation Scheme with Authentication and Authorization for IoT-Based Healthcare

Security of internet of things based on cryptographic algorithms: a survey

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